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18th International Conference on Pattern Recognition (ICPR'06) Volume 3
Facial Feature Selection Based on SVMs by Regularized Risk Minimization
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
ASCII Text
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Weihong Li, Weiguo Gong, Liping Yang, Weimin Chen, Xiaohua Gu, "Facial Feature Selection Based on SVMs by Regularized Risk Minimization," Pattern Recognition, International Conference on, vol. 3, pp. 540-543, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006.
 
 
BibTex
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@article{ 10.1109/ICPR.2006.540,
author = {Weihong Li and Weiguo Gong and Liping Yang and Weimin Chen and Xiaohua Gu},
title = {Facial Feature Selection Based on SVMs by Regularized Risk Minimization},
journal ={Pattern Recognition, International Conference on},
volume = {3},
year = {2006},
issn = {1051-4651},
pages = {540-543},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.540},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Facial Feature Selection Based on SVMs by Regularized Risk Minimization
SN - 1051-4651
SP540
EP543
A1 - Weihong Li,
A1 - Weiguo Gong,
A1 - Liping Yang,
A1 - Weimin Chen,
A1 - Xiaohua Gu,
PY - 2006
KW - null
VL - 3
JA - Pattern Recognition, International Conference on
ER -
 
Weihong Li, Key Lab of Optoelectronic Technology & Systems of Education Ministry of China
Weiguo Gong, Key Lab of Optoelectronic Technology & Systems of Education Ministry of China
Liping Yang, Key Lab of Optoelectronic Technology & Systems of Education Ministry of China
Weimin Chen, Key Lab of Optoelectronic Technology & Systems of Education Ministry of China
Xiaohua Gu, Key Lab of Optoelectronic Technology & Systems of Education Ministry of China
In this paper we present a method based on SVMs by regularized risk minimization for the facial feature selection aiming at improving performance of the classifier by (1) using WT + KPCA as filter approach to choose a set of more meaningful representatives to replace the original data for feature selection; (2) using SVM RFE iterative procedure as wrapper approach to obtain the optimum feature subset; (3) using regularized risk minimization as feature selection ranking criterion. Experimental results on FERET face database subsets indicate that the proposed method has a significant improvement in the classification accuracy and speed.
Citation:
Weihong Li, Weiguo Gong, Liping Yang, Weimin Chen, Xiaohua Gu, "Facial Feature Selection Based on SVMs by Regularized Risk Minimization," icpr, vol. 3, pp.540-543, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006
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